The specific aim of this proposal is to carry out each year one full-week course in advanced gene mapping at The Rockefeller University in New York. The course will be directed towards advanced researchers who are familiar with the basic aspects of statistical genetics but who need to become more proficient in the application of statistical analysis of complex traits. The course will be held in Weiss Hall at The Rockefeller University which is equipped with 24 PCs which are running under Linux (Gentoo v2.6) operating system and are connected to the internet. Twenty-two participants will be admitted to the course. Travel stipends will be provided to seven of the participants who are either pre-doctoral students or post-doctoral fellows to cover the cost of airfare, hotel and board. The course consists of two components: lectures on important and current topics in gene mapping, as well as hands on exercises to be carried out with the latest software programs. The current emphasis of the course is association analysis, in particular whole genome association data for population and family based data for both qualitative and quantitative traits. In the December 2009 Advanced Gene Mapping Course topics to be covered include: Data quality control and data cleaning; analysis of haplotype data; controlling for population substructure/admixture; imputation of genotype data; meta analysis of genome wide association study data; analysis of rare variants; controlling family wise error rates; permutation; False discovery rate; gene x gene interaction; power analysis and sample size estimation. Programs which will be taught and utilized by the course participants include: R, PLINK, GenABEL, LAMP, MACH, MDR, METAL, P2BAT and QTDT. Since gene mapping is a quickly changing field the topics and analysis programs will be updated and changed annually to reflect the latest developments in the field of statistical genetics. Given the large increases in the amount of genetic data which is generated, it is extremely important to train researchers and give them the necessary information and tools to analyze this data to bring about a better understanding of the etiology of complex traits. RELEVANCE (See instructions): The goal of this grant is to provide training in statistical genetics, in particular in the area of association analysis by providing an annual course to doctoral students and researchers. It is expected that this training will lead to an improvement in the analysis of genetic data, helping researchers develop the necessary skills to localize and isolate genes for complex traits thus increasing knowledge of disease etiology.